CN111424086A - Biomarkers, applications and detection kits for gastric cancer diagnosis and prognosis evaluation - Google Patents

Abstract

Compared with the prior art, the cell factor participates in various immune reactions of tumor immune cell infiltration, can realize the staged development stage of gastric cancer risk from the molecular level, quickly and accurately detect and evaluate gastric cancer prognosis, and effectively improve the sensitivity and specificity of prognosis gastric cancer detection and evaluation.

Description

Biomarkers, applications and detection kits for gastric cancer diagnosis and prognosis evaluation

technical field

The invention belongs to the field of biomedicine, and in particular relates to a biomarker for gastric cancer diagnosis and prognosis evaluation, a method for evaluating gastric cancer prognosis using the marker, and the application of a diagnostic kit, in particular to tumor-infiltrating immune cytokine IL23A as gastric cancer Application of biomarkers and diagnostic kits for diagnosis, treatment and prognosis assessment.

Background technique

Gastric cancer (GC) is one of the most common malignant tumors in the world, and it ranks second in the number of deaths due to cancer in the world. According to the International Agency for Research on Cancer, there are about 1 million new cases of gastric cancer every year in the world, of which more than 800,000 die. With the advancement of treatment and diagnosis technology, a variety of treatment and diagnosis methods continue to emerge, and great improvements have been made in the clinical diagnosis and treatment of gastric cancer. However, due to the heterogeneity and individual differences of cancer, primary gastric cancer is prone to Local recurrence or metastasis, almost 50% of patients experienced postoperative in situ recurrence, ectopic metastasis and chemotherapy-resistant response. The 5-year relative survival rate of most advanced gastric cancer patients is still limited to 20%. Therefore, it is helpful to timely determine the condition of gastric cancer patients and understand the prognosis and survival of patients, which will help to take personalized treatment plans for different patients. Therefore, finding simple and effective biomarkers for the prognosis and diagnosis of gastric cancer patients has important guiding significance for clinical treatment.

The tumor microenvironment (TME) is a complex system that mainly includes extracellular matrix, chemokines, cytokines and non-tumor cells. Tumor infiltrating immune cells (TIICs) are the components of non-tumor cells in the TME and play a key role in promoting and inhibiting cancer growth. The function and composition of TIICs vary subtly according to the body's immune status, and they are independent prognostic factors in various cancer types. Heterogeneous infiltration of TIICs, including T cells, dendritic cells, macrophages, neutrophils, and mast cells, has been found in breast cancer. And found differences in the type, density and location of TIIC in colon cancer tissue, which have good prognostic value. In addition, Klintrup et al evaluated the relationship between the overall inflammatory cell response and the density of different types of TIIC in colon cancer patients. The results showed that a high proportion of mature T cells and dendritic cells and memory T cells in a subset of TIICs generally indicates a favorable prognosis, while an increase in immunosuppressive regulatory T cells is associated with a poor prognosis in colon cancer.

Interleukin 23A (IL23A), also known as IL23P19, encodes an alpha subunit of the heterodimeric cytokine interleukin 23 (IL23), which together with the p40 subunit of interleukin 12 (IL12B) constitutes interleukin 23 (IL23). IL23 acts preferentially on memory CD4(+) T cells, activates the transcriptional activator STAT4, and stimulates the production of interferon-γ (IFNG), which plays an important role in inhibiting the spread of cancer cells in the context of tumor immune cell infiltration. In addition, studies have shown that the interaction between IL23A and macrophages has important implications for cancer immunotherapy. Studies have shown that low concentrations of IL23A can promote the progression of bladder tumors, and high expression of IL23A has a better prognosis. Similar studies have also included that high expression of IL23A may inhibit the metastatic potential of pancreatic cancer and is associated with long-term survival in pancreatic ductal adenocarcinoma. It can be seen that IL23A, as an important factor involved in the response of tumor-infiltrating immune cells, plays an important bridge and pivot role in inhibiting the occurrence and development of tumors.

At present, some related patents on prognostic diagnostic markers of gastric cancer have appeared, including the patent publication No. 201210549153.2, which describes the use of DACT1 in the preparation of a kit for the detection of gastric cancer; the patent No. 201810749863.7 discloses the detection of PDLIM4 gene High expression, to diagnose early gastric cancer in individuals, etc. However, the application of IL23A as a prognostic diagnostic marker for gastric cancer has not been reported yet. Finding more molecular markers with high specificity and sensitivity is of great significance for auxiliary diagnosis and prognostic analysis of gastric cancer.

The main disadvantage of the prior art is that the clinical method for judging the prognosis of gastric cancer patients is mostly to know the patient's condition through regular postoperative review and telephone follow-up, which is relatively passive and is not conducive to the control of the patient's condition. In order to achieve more precise and individualized clinical treatment, it is urgent to discover more biomarkers that can be used for the diagnosis and evaluation of gastric cancer prognosis.

IL23A is a subunit of the important cytokine IL23, which preferentially acts on memory CD4(+) T cells, activates the transcriptional activator STAT4, and stimulates the production of interferon-γ, which directly participates in various inflammatory responses of tumor immune cell infiltration. It plays an important role in inhibiting the spread of cancer cells, and plays an important bridge and pivot role in inhibiting the occurrence and development of tumors. By detecting the expression of IL23A in the cancer tissue of patients with gastric cancer, the status of the patients can be assessed and their prognosis can be judged.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a biomarker, application and detection kit for gastric cancer diagnosis and prognosis evaluation in order to overcome the above-mentioned defects of the prior art.

The object of the present invention can be achieved by the following technical solutions: a biomarker for gastric cancer diagnosis, treatment and prognosis evaluation, using tumor-infiltrating immune cytokine IL23A as a gastric cancer diagnosis, treatment and prognosis evaluation biomarker.

The application of a biomarker for the diagnosis and prognosis evaluation of gastric cancer is to evaluate the prognosis of a patient by detecting the relative expression level of the tumor-infiltrating immune cytokine IL23A.

Specifically include the following steps:

(1) Obtain the total RNA of gastric cancer tissue samples and normal tissue samples, and perform reverse transcription to obtain cDNA;

(2) Design and synthesize qPCR primers for IL23A;

(3) qPCR is performed on cDNA using the primers synthesized in step (2), and the relative expression level changes of IL23A in gastric cancer tissue samples are detected by relative quantitative method.

(4) To analyze the relationship between the expression of IL23A and the survival time of gastric cancer patients, and to evaluate the indication effect of its expression level on the prognosis and survival time of gastric cancer patients.

The gastric cancer tissue samples and normal tissue samples in step (1) are stored in liquid nitrogen or -80°C. The method for obtaining the total RNA of gastric cancer tissue samples and normal tissue samples is a conventional method, such as using TRIzol for extraction; reverse transcription can be performed using PrimeScript ^™ RT reagent kit.

In step (2), the qPCR primers are conventional qPCR primers, including the following qPCR primer sequences:

The change in the relative expression level of IL23A in the gastric cancer tissue sample in step (2) is calculated by the following method: fold change of IL23A expression = 2 to the power of (-ΔΔCt), where ΔΔCt = ΔCt (gastric cancer sample) - ΔCt ( control group cancer samples);

ΔCt (gastric cancer samples)=Ct (IL23A in gastric cancer samples)-Ct (internal reference gene GAPDH in gastric cancer samples);

ΔCt (control sample)=Ct (IL23A in control sample)-Ct (internal reference gene GAPDH in control sample).

The method for detecting the relative expression level of the tumor-infiltrating immune cytokine IL23A also includes detecting the expression level of IL23A gene mRNA; or by using an antibody against IL23A protein to specifically detect the expression level of IL23A protein in tissue.

The method for detecting IL23A gene mRNA expression level includes Northern blot analysis method, in situ hybridization method or custom chip method;

The method for specifically detecting the expression level of IL23A protein in tissue using an antibody against IL23A protein includes immunohistochemical method or immunofluorescence method.

A detection kit comprising the tumor-infiltrating immune cytokine IL23A.

To provide tumor-infiltrating immune cytokine IL23A as a marker for gastric cancer diagnosis, prognosis evaluation and its application. IL23A is a subunit of the important cytokine IL23, which preferentially acts on memory CD4(+) T cells and directly participates in various inflammatory responses of tumor immune cell infiltration, and plays an important role in inhibiting the spread of cancer cells. There are significant differences between human clinical gastric cancer tissue and adjacent tissue, and a specific high expression phenomenon in gastric cancer tissue, which suggests that IL23A has a marker role in cancer diagnosis. At the same time, the prognosis of patients with high IL23A expression in gastric cancer tissue was significantly better than that of patients with low IL23A expression, and there was a statistical difference, indicating that the expression of IL23A can clearly and clearly characterize the prognosis of gastric cancer patients.

Through the application of the tumor-infiltrating immune cytokine IL23A, the invention can realize the grading and stratification of the risk level of gastric cancer at the molecular level, accurately and rapidly detect and evaluate the prognosis of gastric cancer patients, and facilitate the clinical classification of patients with different degrees of prognosis It is beneficial to guide the individualized and precise treatment of gastric cancer patients, and at the same time saves medical costs, and has high clinical application value.

Compared with the prior art, the present invention has the following beneficial effects:

1) The present invention provides a novel tumor-infiltrating immune cytokine marker IL23A for evaluating the prognosis and diagnosis of gastric cancer. It is found for the first time that compared with normal tissues, it is specifically highly expressed in gastric cancer tumors, and its expression level is similar to that of normal tissues. The prognosis and survival of patients are closely related, indicating that the tumor immune infiltration-related factor IL23A can be used as a prognostic and diagnostic marker for gastric cancer.

2) The present invention provides primers, detection methods, prognostic assessment methods and diagnostic kits comprising the above-mentioned biomarkers. By detecting the expression of IL23A in biopsy samples of gastric cancer patients, the prognosis of gastric cancer patients can be quickly, accurately and clearly judged, and guidance for the determination of the patient's treatment plan can be provided.

3) The present invention discloses for the first time the application of IL23A as a gastric cancer prognosis marker and detection marker, which is an important factor in gastric cancer tumor-infiltrating immune cells and directly participates in various immune responses in the gastric cancer microenvironment. Experiments have shown that it can quickly, accurately and conveniently predict the prognosis of gastric cancer, realize the grading and staging of gastric cancer risk from the molecular level, and greatly improve the sensitivity and specificity of gastric cancer prognosis detection and evaluation. It is convenient for clinically classifying and treating patients with different prognoses, which is helpful for guiding individualized and precise treatment of gastric cancer patients, and at the same time, it saves medical costs and has high clinical application value.

Description of drawings

Figure 1 shows the difference analysis of IL23A expression in gastric cancer tissue samples and normal samples from the control group by qPCR.

Figure 2 shows the tissue microarray immunohistochemical staining of 40 pairs of gastric cancer-paracancerous tissues. The selected 4 pairs are shown in the following figure, where a-d are the results of IL23A expression in gastric cancer tissues, and e-h are the results of IL23A expression in paracancerous tissues picture.

Figure 3 is a graph showing the expression of IL23A in 40 pairs of gastric cancer and adjacent tissues using tissue microarray immunohistochemistry, in which the circles represent normal tissues and the squares represent gastric cancer tissues.

Figure 4 is a graph showing the relationship between IL23A expression and survival time in gastric cancer patients using the Kaplan-Meier survival curve method.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

Example 1: Detection of expression levels in collected human gastric cancer tissues and adjacent normal tissues by qPCR

1. RNA extraction

1) Grinding of gastric cancer tissue and adjacent tissue

Wash the mortar, pestle, scissors, scalpel, tweezers, and spoons required for grinding with ultrapure water, bake in a 60°C oven for 3 hours, wrap them with tin foil, and place them in a 180°C oven overnight to bake; Before tissue grinding, the above equipments were pre-cooled in liquid nitrogen; the clinical samples that had been stored in liquid nitrogen were taken out, and soybean-sized tissue pieces were cut into pre-cooled mortars, ground, and supplemented in small amounts and repeatedly. Liquid nitrogen, keep the mortar at ultra-low temperature until grinding to powder, this process generally takes 10-15 minutes; after grinding is complete, add 1 mL of pre-cooled TRIzol to continue grinding, and mix the tissue powder and TRIzol fully; wait until TRIzol is completely melted Then transfer it to a labeled 1.7mL DNase/RNase Free centrifuge tube for RNA extraction. If not used immediately, freeze it in a -80°C ultra-low temperature freezer.

2) Extraction and quality inspection of total RNA

The total RNA was extracted using the method for RNA isolation in the TRIzol manual. The specific steps are as follows:

Place the centrifuge tube containing the tissue lysed by TRIzol at room temperature for 5 min; add chloroform at the ratio of 0.2 mL of chloroform per ml of TRIzol, cover the tube, shake vigorously up and down for 15 s, and then stand for 5 min at 12000 °C at 4 °C. Centrifuge at ×g for 15min; after centrifugation, obvious stratification can be seen, carefully suck the colorless aqueous phase of the supernatant, transfer it to a new 1.7mL DNase/RNase Free centrifuge tube, and press the ratio of 0.5mL isopropanol/mL TRIzol Add isopropanol, invert upside down and mix, let stand at room temperature for 10 min, and centrifuge at 12,000 × g for 10 min at 4°C. It can be seen that there is a white total RNA precipitate at the bottom of the tube; carefully discard the supernatant, add 1 mL of 75 per mL of TRIzol. Add 75% ethanol in the ratio of % ethanol to wash the precipitate, centrifuge at 7500 × g for 5 min at 4°C; aspirate the supernatant, air dry for 5 min-10 min, and add an appropriate amount of DNase/RNase-Free sterile water to dissolve the RNA precipitate. Store at -80°C for immediate use.

After the extraction was completed, the total RNA was quantified using a Nanodrop 2000 ultra-micro spectrophotometer, and then the integrity of the RNA was detected by agarose gel electrophoresis. The specific steps are as follows:

Take 2 μL of the extracted total RNA and quantify it with Nanodrop 2000 after appropriate dilution, and use DNase/RNase-Free sterile water as the calibration solution. The ratio of A260/280 of good quality total RNA should be between 2.0-2.2. A 0.8% agarose gel was prepared, the RNA loading amount was 500-800 ng, the electrophoresis buffer was 0.5×TBE, and electrophoresis was performed at 120V for 20 min, and then observed on a gel imager. The intact RNA sample should show 3 clear bands in the electropherogram, representing 28S rRNA, 18S rRNA and 5S rRNA from top to bottom, of which 28S rRNA should be twice as bright as 18S rRNA.

2. Reverse transcription of total RNA

Use Takara's PrimeScript ^TM RT reagent kit for reverse transcription, including removal of genomic DNA and reverse transcription. The specific steps are as follows:

1) Remove the genomic DNA in the total RNA sample, the system formula is as follows:

5×gDNA Eraser Buffer 2μL gDNA Eraser 1μL Total RNA 1μg RNase free water up to 10μL Total volume 10μL

The reaction was carried out in a PCR machine, and the reaction was carried out at 42 °C for 2 min.

2) Reverse transcription reaction

The total RNA samples were equally divided into two PCR tubes, and the mRNA reverse transcription system was set up on ice. The system recipe is as follows:

Gently mix and immediately place it in a PCR machine for reverse transcription reaction. The reaction conditions are:

45℃ 15min

85℃ 5sec

4℃ 5min

3. qPCR reaction

Take 0.5 μL of reverse transcription product, add it to 19.5 μL RNase free water, and dilute 40 times. Configure the qPCR reaction system as follows:

2 x SsoAdvanced SYBR Green Supermix 5μL cDNA (after dilution) 1μL Forward primer (10μM) 1μL Reverse primer (10μM) 1μL Total volume 10μL

After thorough mixing, centrifuge again, gently flick the tube wall to remove air bubbles. Then put it in the StepOne Plus Real-Time PCR System, set the program and carry out the qPCR reaction. The reaction program is as follows:

4. qPCR data analysis

After the qPCR reaction is completed, the relative expression level of the obtained data is analyzed. The specific calculation process is as follows:

ΔCt (gastric cancer samples) = Ct (IL23A in gastric cancer samples) - Ct (internal reference gene GAPDH in gastric cancer samples)

ΔCt(control sample)=Ct(IL23A in control sample)-Ct(internal reference gene GAPDH in control sample)

ΔΔCt=ΔCt (stomach cancer sample)-ΔCt (control group cancer sample)

Fold change in IL23A expression = 2 to the power of (-ΔΔCt).

The results are shown in Figure 1, the expression of IL23A in gastric cancer tissue samples was significantly higher than that in normal samples of the control group, and the difference was statistically significant (p < 0.01).

The following table shows the qPCR primer sequences used in the experiment:

Example 2. Tissue chip immunohistochemistry was used to detect the expression of gastric cancer tissue and adjacent normal tissue:

1. Frozen sections of gastric cancer tissue and adjacent tissue

Mark the OCT embedding medium (opti-mum cutting temperature compound) on the fixation head, and then take a suitable size of tissue (about 24×24×3mm, not embedded) and place it on the OCT. The surface of the tissue is exposed outside the OCT. The tissue was completely embedded with OCT. The fixed head is placed on the quick-cooling table in the freezer, and frozen at about -25°C for 10 minutes (the time may vary slightly depending on the tissue, and the time may be longer for larger tissue or adipose tissue, generally about 10 minutes). Clamp the frozen head to the microtome, fix the angle of the high-speed knife, use the fine adjustment to level the tissue to expose the maximum section, adjust the fine-tuning scale to 5μm, put down the anti-roll plate and start slicing, moving at a constant speed in the same direction. Turn the lever. After cutting, open the anti-roll plate, unfold the tissue with a writing brush, carefully paste it on the glass slide, arrange it in order, and store it in air-drying and low-temperature storage.

2. Immunohistochemical staining of gastric cancer and adjacent tissues

Fix the slides with 4% paraformaldehyde or 10% formalin for 30 min. After fixation, wash five times with PBS for 5 min each time. Add 1 part of 30% H ₂ O ₂ + 50 parts of methanol to mix, soak at room temperature for 30 minutes to inactivate endogenous peroxidase, and wash with distilled water 5 times. Block with 5% BSA for 1.5h in a wet box, the amount of BSA is about 300-400 μL per sheet, and the liquid is gently wiped dry after the end. In the wet box, add primary antibody rabbit monoclonal antibody (Bs-18146r, Bioss), dilute with 1% BSA, the dilution ratio is 1:200, and react at room temperature for 1-1.5 hours. After the reaction, the cells were washed with PBS for about 1 h, and finally the liquid was gently wiped dry. In the wet box, add secondary antibody Goat-anti-Rabbit-IgG-HRP, dilute with 1% BSA, the dilution ratio is 1:100, and react at room temperature for 30 minutes. After the reaction, wash with PBS for about 2h, and finally dry the liquid gently.

Color development: Add DAB to react for 2-3 minutes, when the sample turns yellow, place it in running water for 30s, stop the reaction, and protect from light.

Staining: immersed in 0.1-1ug/mL DAPI, stained for 1min, rinsed three times with PBS.

Dehydrated and transparent mounting slides: 75% ethanol for 20s→85%ethanol for 30s→95%ethanol for 1min→95%ethanol for 1min→anhydrous ethanol for 2min*2 times→xylene for 2min*2 times, neutral resin for sealing, the mounting medium should be Appropriate amount, being careful not to create air bubbles.

3. Immunohistochemical scanning and quantitative analysis of tissue chips

Scan the tissue chip with a tissue chip scanner (Pannoramic MIDI, 3D HISTECH), the chip will gradually move under the lens of the scanner, and image while moving, and then scan and image all the tissue information on the tissue slice to form a file. This file contains all the tissue information on the tissue section, as shown in Figure 2.

After the image scanning is completed, enter the TMA software of the Quant center analysis software, set the diameter of the chip tissue point and the number of rows and columns, and the software will automatically generate a number. The densito quant software in the Quant center was used to automatically identify and set all dark brown nuclei as strong positive, brown yellow as moderate positive, light yellow as weak positive, and blue nuclei as negative. Then, each tissue point was identified and analyzed to determine the area of strong positive, moderate positive, weak positive and negative (unit: pixel), the percentage of positive, and finally the H-SCORE score was performed. H-SCORE (histochemistry score) is a histological scoring method for processing the results of immunohistochemistry. The number of positive cells and their staining intensity in each section are converted into corresponding values to achieve the purpose of semi-quantitative tissue staining. The calculation formula is H-SCORE=∑(PI×I)=percentage of positive cells to all cells in the section (PI)×staining intensity (I).

4. Analysis of the clinical significance of IL23A expression in cancer tissues combined with the clinical survival information of gastric cancer patients

IL23A expression was assessed by two-tailed paired t-test using GraphPad Prism 5 software. p<0.05 was considered statistically significant and all analyses were performed using R software (updated version 3.5.2). The expression levels of IL23A in 40 pairs of gastric cancer and adjacent tissues are shown in Figure 3. The difference in IL23A expression between gastric cancer tissues and adjacent tissues was statistically significant (p<0.01), and its expression in gastric cancer tissues was significantly higher than that in adjacent tissues. Taking the H-SCORE expression value in the above experiments as the reference standard, and based on the median value of gene expression, 40 patients with gastric cancer were divided into IL23A high expression group and IL23A low expression group, and combined with their survival data, the Kaplan-Meier was drawn. The survival curve, the analysis results are shown in Figure 4. The survival time of gastric cancer patients with high IL23A expression was significantly longer than that of gastric cancer patients with low IL23A expression, and the difference was statistically significant (p < 0.01), which indicated that IL23A has important significance in the prognosis evaluation of gastric cancer, and can be used as the diagnosis, treatment and prognosis of gastric cancer patients. landmark.

The present invention is not limited to the above-mentioned embodiments, and improvements and modifications made by those skilled in the art according to the disclosure of the present invention without departing from the scope of the present invention should all fall within the protection scope of the present invention.

Claims (10)

1. A biomarker for diagnosis, treatment and prognosis evaluation of gastric cancer, characterized in that IL23A, a tumor-infiltrating immune cytokine, is used as the biomarker for diagnosis, treatment and prognosis evaluation of gastric cancer. 2 . The application of a biomarker for the diagnosis, treatment and prognosis assessment of gastric cancer according to claim 1 , wherein the prognosis of a patient is assessed by detecting the relative expression level of the tumor-infiltrating immune cytokine IL23A. 3 . 3. The application of the biomarker for gastric cancer diagnosis and treatment and prognosis evaluation according to claim 2, wherein the detection method of the relative expression level of the tumor-infiltrating immune cytokine IL23A is a qPCR method, which specifically comprises the following steps : (1) Obtain the total RNA of gastric cancer tissue samples and normal tissue samples, and perform reverse transcription to obtain cDNA; (2) Design and synthesize qPCR primers for IL23A; (3) qPCR is performed on cDNA using the primers synthesized in step (2), and the relative expression level changes of IL23A in gastric cancer tissue samples are detected by relative quantitative method. 4 . The application of the biomarker for diagnosis, treatment and prognosis evaluation of gastric cancer according to claim 3 , wherein the gastric cancer tissue sample and normal tissue sample in step (1) are stored in liquid nitrogen or -80°C. 5 . 5. the application of the biomarker for gastric cancer diagnosis and treatment and prognosis assessment according to claim 3, is characterized in that, in step (2), qPCR primer is conventional qPCR primer, comprises following qPCR primer sequence:

6. The application of the biomarker for gastric cancer diagnosis and treatment and prognosis assessment according to claim 3, wherein the relative expression level change of IL23A in the gastric cancer tissue sample of step (2) is calculated by the following method: IL23A The fold change of expression = 2 to the power of (-ΔΔCt), where ΔΔCt = ΔCt (gastric cancer sample) - ΔCt (control group cancer sample); ΔCt (gastric cancer samples)=Ct (IL23A in gastric cancer samples)-Ct (internal reference gene GAPDH in gastric cancer samples); ΔCt (control sample)=Ct (IL23A in control sample)-Ct (internal reference gene GAPDH in control sample). 7. The application of the biomarker for gastric cancer diagnosis, treatment and prognosis evaluation according to claim 2, wherein the method for detecting the relative expression level of the tumor-infiltrating immune cytokine IL23A further comprises detecting the expression of IL23A gene mRNA or by using an antibody against IL23A protein to specifically detect the expression level of IL23A protein in tissue. 8. The application of the biomarker for gastric cancer diagnosis and treatment and prognosis assessment according to claim 7, wherein the method for detecting IL23A gene mRNA expression level comprises Northern blot analysis, in situ hybridization or custom chip method; The method for specifically detecting the expression level of IL23A protein in tissue using an antibody against IL23A protein includes immunohistochemical method or immunofluorescence method. 9. The application of the biomarker for gastric cancer diagnosis and treatment and prognosis evaluation according to claim 2, wherein the relationship between the expression of IL23A in gastric cancer patients and the survival period is analyzed, and its expression level is evaluated for the prognosis and survival of gastric cancer patients. period indication. 10. A detection kit comprising the tumor-infiltrating immune cytokine IL23A.

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